A two-stage subspace trust region approach for deep neural network training. - Viacheslav Dudar; Giovanni Chierchia; Emilie Chouzenoux; Jean-Christophe Pesquet; Vladimir Semenov (EUSIPCO, 2017)

Use of symmetric kernels for convolutional neural networks. - Viacheslav Dudar; Vladimir Semenov (CoRR, 2018)

Convergence of Adaptive Methods for Equilibrium Problems in Hadamard Spaces. - Vladimir Semenov; Yana Vedel (IT&I Workshops, 2020)

Adaptive Extraproximal Algorithm for the Equilibrium Problem in Hadamard Spaces. - Yana Vedel; Vladimir Semenov (OPTIMA, 2020)

Convergence of Adaptive Forward-Reflected-Backward Algorithm for Solving Variational Inequalities. - Sergey Denisov; Vladimir Semenov (IntSol Workshops, 2021)

Theoretical Bound of the Complexity of Someextragradient-Type Algorithms for Variational Inequalities in Banach Spaces. - Serhii Denysov; Vladimir Semenov (IT&I Workshops, 2021)

Convergence of Adaptive Operator Extrapolation Method for Operator Inclusions In Banach Spaces. - Vladimir Semenov; Serhii Denysov (CMIS, 2022)

Optically addressed spatial light modulators as generic dynamical systems for novel computing substrates. (Modulateurs spatiaux de lumière tout-optique destinés à la conception de nouveaux processeurs basés sur des systèmes dynamiques complexes). - Vladimir Semenov (2022)

Optimizing Network Economics Problem with Adaptive Algorithms for Variational Inequalities. - Vladimir Semenov; Serhii Denysov (DSMSI (1), 2023)

The Regularized Operator Extrapolation Algorithm for Variational Inequalities. - Vladimir Semenov; Oleh Kharkov (DSMSI (2), 2023)